The rush to implement artificial intelligence risks missing the fundamental point about technology adoption, according to one industry expert with deep experience in both AI and real estate.
“The market needs tools that integrate AI into a value chain and AI existing as a horizontal or as a feature is only useful for so long,” says David Selinger, CEO of Deep Sentinel and former Amazon AI team leader. “People get tired of it, and then they start thinking about how do I integrate it into my workflow?”
The Evolution of AI Adoption
Drawing on his experience building Amazon’s first AI-focused team and founding multiple technology companies, Selinger sees clear patterns in how new technologies gain lasting adoption.
“When you look at the curve of technology adoption for society in the early days, we can get really excited about it without that,” Selinger explains. “People are early adopters and they’re excited about it and it doesn’t really matter if it provides net utility.”
However, this enthusiasm has limits. “After a period of time, people kind of look at their lives and they say, ‘I need to go back to doing what I did. Otherwise, I’m not going to be feeding my kids or getting them to their activities or getting paid at my job,’” Selinger notes.
Learning from Consumer Tech
Selinger points to major tech companies as examples of successful AI integration. “If you look at what Microsoft is doing, what Open AI is doing, what Amazon’s doing, what Facebook’s doing, Apple is a great example of a company that’s really trying to make AI a part of the workflows,” he says.
He cites Apple’s photo editing features as an example: “The most recent Apple AI features that are getting used a lot are the things that are integrated into the workflows that people are already used to doing.”
Applying These Lessons to Security
In the security space, this means combining AI capabilities with human judgment rather than trying to fully automate. “We use AI to drive up the quality of having a human being watching a video feed and simultaneously drive down the cost by hundreds of times,” Selinger explains.
This hybrid approach allows for what Selinger calls “the complete end-to-end solution,” one that maintains human oversight while leveraging AI’s capabilities for continuous monitoring and rapid response.
While his company represents one implementation of this philosophy, Selinger argues the principle applies broadly: technology should enhance rather than replace human capabilities in critical decision-making roles.
